Special Issue: Machine Learning in Process Control and Systems Engineering
• 大类 : 工程技术 - 3区
• 小类 : 工程：化工 - 3区
The application of data-based machine-learning tools, together with chemical engineering and systems engineering principles, to the analysis, control and optimization of chemical process, energyand water systems is an emerging multi-disciplinary research area that ties together data-science,nonlinear dynamics, control theory, optimization and chemical engineering science. Motivated bythe fundamental and practical challenges associated with this problem, research in this area haswitnessed significant developments over the past few years. This progress encompasses both theoretical advances and practical applications and has been well documented by a large and growing number of technical sessions and tutorial workshops in the context of major chemical engineering and process systems and control engineering conferences. For example, several successful sessions and tutorial workshops on the modeling, control and optimization of energy systems have recently been organized and held by the Computing and Systems Technology (CAST) Division at the 2017, 2018 and 2019 AIChE Annual Meetings. Similar sessions have also been organized by chemical engineering researches in the context of major control engineering conferences, such as 2018 and 2019 American Control Conferences, and process systems engineering conferences like 2019 FOCAPD. These sessions attracted a lot of chemical engineering researchers and stimulated numerous interesting exchanges of ideas. Similar sessions are planned for future meetings.
Given the enormous diversity of process systems, the development of systematic tools and methods for the machine-learning-based analysis, control and optimization of such systems is a challenging task that encompasses a broad set of problems requiring an integrated set of skills across various disciplines. However, it is also an appealing goal because the diverse community of scholars making advances in these areas offers a unique opportunity to promote the intellectual exchange needed to reap the benefits of varied advances with an eye to the fundamental commonalities rooted in chemical and systems engineering principles. Due to this diversity, this goal is not currently addressed by any single journal in either control theory, systems engineering or chemical engineering.